Terminal State Detection for High-Speed Train Boarding and Exit
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Solution Overview
Problem
Conventional methods for identifying a high-speed train user's terminal state are limited, failing to accurately determine whether a user is getting on or off a high-speed train, thereby affecting user experience.
Innovation Solution
A terminal state identification method using acceleration data to determine probability values for walking and high-speed train states, combined with network connection data to enhance accuracy, and providing tailored interfaces and services based on these states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dedicated high-speed railway network is used to identify terminal users, then high-speed train users can be identified, but the capability to accurately identify terminal state (getting on/off train) is very limited
Solution Approach 1:
The patent combines multiple identification methods (acceleration sensor data, network connection data, location data) into a unified terminal state identification system. The processing unit integrates data from these different sources to determine probability values for walking state and high-speed train state, achieving accurate state identification without requiring a complex dedicated system for each individual data source.
Solution Approach 2:
The identification system is designed to handle multiple functions: it can identify both high-speed train users and determine their terminal states (getting on/off train). The processing unit uses the same acceleration and network data to perform both identification tasks, making the system multi-functional and reducing overall complexity.
2Measurement precision
If multiple data sources (acceleration, network connection) are combined to enhance identification accuracy, then state recognition accuracy improves, but computational complexity and processing requirements increase
Solution Approach 1:
The patent segments the identification process into distinct probability calculations: a first probability value for walking state and a second probability value for high-speed train state. The processing unit separately analyzes acceleration data and network connection data for each probability, then combines these segmented results to determine the final terminal state. This segmentation makes the complex processing more manageable and efficient.
Solution Approach 2:
The system transforms raw sensor data and network data into probability parameters (first probability value and second probability value). By changing the data representation from raw measurements to probability values, the system simplifies the comparison and decision-making process, reducing computational complexity while maintaining high accuracy.
3Measurement precision
If probability-based state determination is used, then accurate distinction between walking state and high-speed train state is achieved, but the system requires continuous data collection and processing
Solution Approach 1:
The processing unit performs probability calculations and state determinations at periodic intervals rather than continuously. The system collects acceleration data and network connection data, processes them to update probability values, and determines terminal states at discrete time points. This periodic processing reduces energy consumption compared to continuous analysis while maintaining accurate state recognition.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately identifies high-speed train states, enabling personalized recommendations and network optimizations, improving user experience during high-speed train travel.
Implementation Method 1
obtaining acceleration data of a terminal by using an acceleration sensor
Data Source
Figure 1(1)~1(2)
Figure 2(1)~2(2)
Figure 3
AI summary
A terminal state identification method and apparatus are provided, and are applied to the field of terminal technologies. The method includes: determining a first probability value based on acceleration data; determining a second probability value based on the acceleration data; determining a state of a terminal user based on the first probability value and the second probability value, where the state of the terminal user includes a first state, a second state, and a third state, the first state is a state in which the terminal user leaves a high-speed train carriage, the second state is a state in which the terminal user is located in a high-speed train carriage and a high-speed train is driving, and the third state is a state in which the terminal user is located in a high-speed train carriage and a high-speed train stops running; and displaying a first interface when determining that the terminal user is in the first state, where the first interface includes a first window, and the first window is used to display travel recommendation information for a current location to the user. In this way, a scenario in which the terminal user gets on/off a high-speed train carriage can be intelligently identified, to recommend a corresponding function to the user and improve experience of using an intelligent terminal when the user takes a high-speed train.